Centrum: Model-based Database Auto-tuning with Minimal Distributional Assumptions

Summary: Centrum is a model-based DBMS auto-tuner using two-phase boosting ensembles with distribution-free interval estimation via conformal prediction. Fuse gradient boosting with conformal inference in BO; it outperforms 21 SOTA tuners on two DBMSs across three workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 7019
Venue: SIGMOD
Year: 2025
Pagerank: 4.1945683e-05
Overall Rank: 10,370 | 27.86%
DOI: 10.1145/3709671

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036721403
424	Tuning Database Configuration Parameters with iTuned	2009	VLDB	0.00023616398
514	An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning	2019	SIGMOD	0.0002124895
782	QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning	2019	VLDB	0.00016729063
1,902	Black or White? How to Develop an AutoTuner for Memory-based Analytics	2020	SIGMOD	0.00010157713
3,522	ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases	2021	SIGMOD	7.0096727e-05
3,812	Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation	2022	VLDB	6.7373184e-05
4,265	CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions	2021	VLDB	6.3097793e-05
4,380	LlamaTune: Sample-Efficient DBMS Configuration Tuning	2022	VLDB	6.2396606e-05
4,842	Towards Dynamic and Safe Configuration Tuning for Cloud Databases	2022	SIGMOD	5.8826802e-05
5,833	LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications	2022	SIGMOD	5.3106182e-05
6,885	PilotScope: Steering Databases with Machine Learning Drivers	2024	VLDB	4.895386e-05

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